ΑΙhub.org
 

AI4Industry pilot releases first demonstration video


by
08 February 2021



share this:
AI4industry video capture
Screengrab from the demonstration video produced by AI4Industry

By AI4EU’s AI4Industry pilot team

AI4EU’s pilot AI4Industry released its first video to demonstrate how AI techniques can help develop flexible and transparent manufacturing. The techniques, including semantic technologies, answer set programming, and machine learning, are demonstrated in an experimental plant provided by Evosoft.

The AI4Industry pilot aims to create a tool that assists engineers in production planning, getting insights about potential problems in manufacturing, and estimating the time needed to complete an incoming product request.

The tool consists of 3 main parts: skill matching and explanations, planning, and time prediction. Skill matching represents producibility checking, i.e. checking whether a certain product can be produced by the set of available machines in the factory.

The explanations function provides a list of statements that presents the reasons why a certain product cannot be produced, essentially explaining to humans why production stops. The planning function creates a list of steps that are needed to manufacture a product. Introduced as a small modification to the planning technique, the plan repair program provides explanations to humans of issues in the factory or the production goal.

Finally, how does the planner know how much time production will take? The time prediction component, which based on a machine-learning algorithm, estimates the production time per product. We show the experimental factory of Evosoft producing caps on cans with different colours and the results of these methods in a basic mock-up UI.

The AI4Industry pilot, a collaboration between Siemens AG, TU Wien, and Fraunhofer IAIS, is one of the eight pilots to be carried out during the lifetime of the AI4EU project to provide insights on real scenarios in the selected areas.




AI4EU

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Deep learning-powered biochip to detect genetic markers

System can detect extremely small amounts of microRNAs, genetic markers linked to diseases such as heart disease.

Half of AI health answers are wrong even though they sound convincing – new study

  12 May 2026
Imagine you have just been diagnosed with early-stage cancer and, before your next appointment, you type a question into an AI chatbot.

Gradient-based planning for world models at longer horizons

  11 May 2026
What were the problems that motivated this project and what was the approach to address them?

It’s tempting to offload your thinking to AI. Cognitive science shows why that’s a bad idea

  08 May 2026
Increased offloading to new tools has raised the fear that people will become overly reliant on AI.

Making AI systems more transparent and trustworthy: an interview with Ximing Wen

  07 May 2026
Find out more about Ximing's work, experience as a research intern, and what inspired her to study AI.

Report on foundation model impacts released

  06 May 2026
Partnership on AI publish a progress report on post-deployment governance practices.

Forthcoming machine learning and AI seminars: May 2026 edition

  05 May 2026
A list of free-to-attend AI-related seminars that are scheduled to take place between 5 May and 30 June 2026.

AI for Science – from cosmology to chemistry

  01 May 2026
How AI is transforming science, from a day conference at the Royal Society



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence